See how to type your first few lines of Julia code. You'll also learn some key concepts behind the Julia language: Optional Static Typing, multiple dispatch, vectorized operations, and find out what a homoiconic language is. Enjoy!

Thursday, March 19, 2015

"Julia is a fresh approach to technical computing." boasts the startup message, flourished with colorful circles hovering above a bubbly ASCII Julia logo. The formatting effort is not wasted, it's an exuberant promise: Julia will make the command line fun again.

Julia was created by four Data Scientists from MIT who began working on it around 2011. The language is beginning to mature at a time when the Data Scientist job title is popping up on resumes as fast as Data Scientist jobs appear. The timing is excellent. R programming, an offshoot of S Programming , is the language of choice for today's mathematical programmer. But it feels clunky, like a car from the last century. While Julia may not unseat R in the world of Data Analysis, plans don't stop there.

If you want to code along with the examples in this article, jump to Getting Started with Julia and chose one of the three options to start coding.

Julia is a general purpose programming language. It's creators have noble goals. They want a language that is fast like C, they want it flexible with cool metaprograming capabilities like Ruby, they want parallel and distributed computing like Scala, and true Mathematical equations like MATLAB.

Why program in Julia?

1) Julia is Fast

Julia already boasts faster matrix multiplication and sorting than Go and Java. It uses the LLVM compiler, which languages like GO use for fast compilation. Julia uses just in time (JIT) compilation to machine code , and often achieves C like performance numbers.

2) Julia is written in Julia

Contributors need only work with a single language, which makes it easier for Julia users to become core contributors.

"As a policy, we try to never resort to implementing things in C. This keeps us honest – we have to make Julia fast enough to allow us to do that" -Stephan Karpinski

And, as the languages co-creator Karpinski notes in the comments of the referenced post, Writing the language itself in Julia means that when improvements are made to the compiler, both the system and user code gets faster.

3) Julia is Powerful

Like most programming languages, it's implementation is Open Source. Anyone can work on the language or the documentation. And like most modern programming languages, Julia has extensive metaprogramming support. It's creators attribute the Lisp language for their inspiration:

Like Lisp, Julia represents its own code as a data structure of the language itself.

a) Optional Strong Typing
Using strong typing can speed up compiling, but Julia keeps strong typing optional, which frees up programmers who want to write dynamic routines that work on multiple types.

c) Multiple Dispatch

Multiple dispatch allows Object Oriented behavior. Each function can have several methods designed to operate on the types of the method parameters. The appropriate method is dispatched at runtime based on the parameter types.